The reason LLMs suck in plenty of brownfield projects is because those codebases likely either implemented frameworks in a proprietary way, maybe did not rely o

The reason LLMs suck in plenty of brownfield projects is because those codebases likely either implemented frameworks in a proprietary way, maybe did not rely on any public framework at all, or were in general done in an esoteric way and therefor few (if any) similar codebases exist within the LLMs training data. Which is problematic because LLMs aren't capable of reasoning or learning they're literally just predicting the next most likely token in a chain similarly to how autocomplete works. Without you supplying additional context and explicitly defining guardrails for preforming common tasks the LLM has no frame of reference for working with your codebase.